Deep learning is rapidly becoming the most popular topic in the industry. This book introduces trending deep learning concepts and their use cases with an industrial- and application-focused approach. You will cover a range of projects covering tasks such as mobile vision, facial recognition, smart AI assistants, and augmented reality.
With the help of eight projects, you will learn to integrate deep learning processes into the iOS and Android mobile platforms. This will help you to transform deep learning features into robust mobile apps efficiently. This book gets you hands-on with selecting the right deep learning architectures and optimizing mobile deep learning models while following an application-oriented approach to deep learning on native mobile apps. We will later cover various pretrained and custom-built deep learning model-based APIs, such as the ML Kit through Google Firebase. Further on, the book will take you through examples of creating custom deep learning models with the help of TensorFlow Lite using Python. Each project will demonstrate how to integrate deep learning libraries into your mobile apps, right from preparing the model through to deployment.
By the end of this book, you'll have the skills to build and deploy advanced deep learning mobile applications on both iOS and Android.
